The Metropolitan Police of London (MET) is exploring the use of artificial intelligence (AI) as a key tool to combat child sexual abuse, especially in the digital realm, where this type of crime is growing rapidly. The main objective is to improve the ability to identify victims more quickly and efficiently, while reducing the emotional impact that manually reviewing large volumes of highly traumatic material has on investigators. 

Traditionally, officers have had to spend many hours examining seized images and videos to determine whether they are linked to known cases or if they point to new victims. This process is not only slow but also psychologically very demanding. With the introduction of AI, MET aims to automate part of this task through systems capable of analysing large amounts of content in a short time, identifying patterns, classifications, and possible indications of unidentified victims. This would allow to prioritise cases with higher risk and accelerate protection interventions. 

According to recent data, the MET investigated over 5,400 child sexual abuse crimes in a year, with more than 1,300 children needing protection in cases related to online sexual exploitation. This phenomenon, known as OCSAE (Online Child Sexual Abuse and Exploitation), has increased by 25% year-on-year and represents a significant part of the national police burden. In this context, the need for new technological tools becomes critical for managing the volume and complexity of cases. 

AI could also help classify material according to its severity (categories A, B, and C), highlighting the most urgent cases—especially those in category A, which include more severe cases of abuse—for immediate intervention. In addition, the MET is testing other technologies capable of reviewing hundreds of thousands of messages in a matter of minutes, a task that would manually require days or weeks. 

Despite the potential benefits, the MET has emphasised that any use of AI will be conducted within strict legal and ethical frameworks, with constant human oversight. Specialised officers will continue to be responsible for decision-making, ensuring that the technology is used as support and not as a substitute for professional judgement. 

Alongside technological innovation, the MET is also investing 10 million pounds in improving interview spaces for child victims. These rooms, known as VRI (Visual Recorded Interviews), are designed to provide safe, comfortable environments tailored to the needs of children, including those with disabilities or neurodiversity. The objective is to reduce the trauma associated with the statement and improve the quality of witnesses, as it has been shown that children provide clearer accounts when they feel safe and supported. 

The new facilities include adjustable furniture, spaces for play and drawing, and educational resources adapted to different ages. This child-centred approach is part of a broader strategy that also includes training thousands of agents in trauma-sensitive communication and expanding specialised teams in child exploitation. 

Despite these advances, experts and officials in the field of victims remind us that the improvement of infrastructure and technologies is only part of the solution. One of the major challenges is still ensuring that victims receive ongoing support and are treated with dignity throughout the judicial process, as many abandon before legal decisions are made. 

In conclusion, the combination of artificial intelligence and investment in more human environments represents a significant shift in the way law enforcement addresses child sexual abuse. This integrated approach not only seeks to increase operational efficiency but also to place the well-being of victims and professionals at the centre of the police response. 

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The analysis of fingerprints continues to be one of the most relevant tools in criminal investigations, but it is also a complex process that requires great precision and expertise. In this context, the National Institute of Standards and Technology (NIST) in the United States has taken an important step to modernise this field with the launch of new resources that combine big data and open-source technology.

NIST has recently completed its Special Database 302 (SD 302), a set that includes approximately 10,000 fingerprints collected in controlled environments from 200 volunteers. Although this database has existed since 2019, until now only a portion of the images had detailed annotations. With this new update, all fingerprints have been completely annotated, significantly increasing their value for research and training.

These annotations are especially relevant because they indicate the quality of different areas of each imprint using colour codes. In practice, this allows for easier identification of which parts of a fingerprint contain useful information for identification and which may be less reliable. This distinction is fundamental for both human examiners and automated systems, as the fingerprints collected at crime scenes are often incomplete, blurred, or partially deteriorated.

From the perspective of security and forensic investigation, the availability of a fully annotated dataset represents a key advancement. It not only facilitates the training of new professionals, but also allows for the development and validation of artificial intelligence algorithms with a solid empirical foundation. At a time when AI plays an increasing role in the analysis of digital evidence, having quality data is essential to ensure reliable and reproducible results.

At the same time, NIST has released a new open-source software called OpenLQM, an evolution of a tool previously used by law enforcement in the United States. This software is designed to automatically assess the quality of fingerprints. Its operation is relatively simple: it analyses an image and assigns a score between 0 and 100 that reflects the level of detail and usefulness of the imprint.

This functionality has very important practical implications. In a real investigation, analysts may encounter hundreds of fingerprints collected at the same scene. Automatically classifying them according to their quality allows to prioritise those that are more likely to lead to a positive identification, thus reducing the time and resources required. Moreover, the use of an objective metric helps improve consistency among different examiners, a critical aspect in judicial processes.

Another notable element is that OpenLQM is open-source and compatible with multiple operating systems, including Windows, Mac, and Linux. This facilitates its global adoption by both law enforcement agencies and research centres and universities. This openness also fosters transparency and collaboration, two values that are becoming increasingly important in the development of technologies applied to security.

Overall, the combination of the fully annotated SD 302 dataset and the Open LQM software provides a powerful platform for advancing the science of fingerprint identification. These resources not only enhance the tools currently available, but also lay the groundwork for future innovations in the field of digital forensics and security.

Ultimately, the NIST initiative exemplifies how the integration of quality data, open tools, and artificial intelligence can transform traditional processes and enhance their efficiency and reliability. For security professionals, these advancements represent a clear opportunity to enhance analytical capabilities and adapt to an increasingly technological and demanding environment.

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The National Institute of Standards and Technology (NIST) and its partners at the University of Colorado Anschutz have made the first measurement of tetrahydrocannabinol (THC) in the breath of individuals who have consumed edible cannabis.

This research supports public safety and law enforcement, as there is still no reliable evidence in place to determine when a person has consumed cannabis or whether they are intoxicated as a result of its use.

NIST researchers have observed increases and decreases in THC levels in the breath of participants several hours after consuming cannabis-infused gummies.

Cannabis use has increased in the U.S. and has exceeded alcohol as a daily recreational drug for Americans. Nearly 20% of cannabis consumers have admitted to driving after consuming it. However, unlike alcohol, there is no reliable evidence regarding cannabis consumption. Even blood tests cannot determine whether a person has consumed it. This means that law enforcement cannot verify a person’s recent usage, let alone the level of intoxication.

To complicate matters further, there are multiple ways to consume cannabis: smoking, vaping, ingesting, and dabbing (inhaling a concentrated form of cannabis extracts). Scientists know that the psychoactive component THC shows up in breath after smoking, but what happens with edible formats?

The answer is that after consuming these other forms of cannabis, THC is also present in breath. In a study published in the Journal of Analytical Toxicology researchers at the NIST have taken the first samples of cannabinoids in breath after study participants ingested cannabis-infused edibles.

Making a breathalyzer for cannabis is more difficult than making one for alcohol. Alcohol is a relatively simple and highly volatile molecule: it easily travels through the lungs and evaporates when it comes into contact with air. However, THC is a more complicated molecule with very low volatility. Consumption is usually hundreds of times less than that of alcohol. It appears in very small concentrations in breath, making THC detection much more difficult. Regular cannabis users can have THC in their breath for at least eight hours and in their blood for weeks after they stop using it. This means that a single measure is insufficient to determine when a person last consumed it.

In the new study, NIST partners at the Anschutz Medical Campus of the University of Colorado observed 29 participants consuming a cannabis-infused gummy in the laboratory. The edibles contained between 5 and 100 milligrams of THC. The researchers first took a breath sample from the participants before they ingested the product. They then observed each participant for three hours and collected breath samples approximately every hour.

NIST researchers measured the concentration of THC and other cannabinoids in breath at these intervals. THC was detected in the majority of participants before they consumed the edible, even though they had been asked to abstain for eight hours prior to the study. This is not surprising. Our body processes cannabinoids slowly and takes weeks to eliminate them from our system compared to how quickly alcohol is processed.

This study shows that THC ingested in edible form can pass through the digestive system and be exhaled again by the lungs.

This research supports the idea that multiple breath samples over a period of time could be a way to use a breathalyzer to detect cannabis consumption, regardless of how it is ingested. However, devices will still require standards that ensure their accuracy and proper usage.

Researchers: Jennifer L. Berry, Ashley Brooks-Russell, Tara M. Lovestead, and Kavita M. Jeerage. The detection of cannabinoids in breath after ingestion of cannabis-infused edibles. Journal of Analytical Toxicology. Published online on 10 July 2025. DOI: 10.1093/jat/bkaf063

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Artificial intelligence (AI) is rapidly changing several sectors, including public safety. As technology advances, new opportunities present themselves for police to become more efficient and better able to respond to emergencies.

In this context, the idea of an AI lab for the police gains interest as a way to explore and apply AI solutions responsibly.

Recently, the UK government published a case study on how a police AI lab could work, offering lessons that may be useful for any agency looking to integrate AI into security.

Why an AI lab for the police? AI can bring a lot to the police in a variety of areas:

• Data analysis. The police manage huge amounts of data, such as crime reports and security camera images. AI can help process this data quickly and identify patterns that might go unnoticed.
• Crime prediction and prevention. With predictive analytics, AI can help detect areas or times with a higher probability of criminal activity, which would allow for improved resource allocation.
• Resource optimisation. AI can help manage patrol routes and assign personnel, which would improve their efficiency.
• Research support. AI tools can streamline evidence review and suspect identification, leaving more time for more complex tasks.
• Improved decision making. AI can provide data-driven insights and analytics that help officers make more informed decisions.

However, applying AI in an area as sensitive as public safety comes with some challenges. Aspects such as privacy, bias in algorithms, transparency and accountability need careful attention. This is where an AI lab can be useful.

The UK case study describes a model for an AI lab that focuses not only on technology, but also on governance and collaboration. Some of the important points are:

1. Multidisciplinary collaboration. The creation of an AI lab should bring together different experts: criminologists, ethicists and experienced police officers. This ensures that the solutions are technically sound and practical.

2. Ethics and governance. Before starting, it is necessary to establish a good ethical framework. This includes defining principles on the responsible use of AI and ensuring data privacy.

3. Agile methodology. AI projects should be flexible, start with small trials, collect feedback and be adapted before wider implementation.

4. Collaboration with the community. Public trust is key. An AI lab should seek feedback and engage with the community to address privacy concerns.

5. Real needs. AI solutions must address real needs that officers have identified. The laboratory must work to solve concrete problems.

6. Training. Not only do you need technology, but you also need officers to understand how these tools work. The laboratory should have training programmes.

7. Transparency. Decisions made with AI must be understandable. It is important that there is accountability in case of errors.

In conclusion, the adoption of artificial intelligence in the field of public safety is inevitable. However, the way in which this adoption is approached is crucial.

A well-planned AI lab, with a strong commitment to ethics, transparency and collaboration, can ensure that AI becomes a powerful tool for the common good, while strengthening security and maintaining citizen trust. The British model provides a valuable compass for navigating the road to the future of policing.

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Forensic science plays a critical role in criminal justice, but the influence of human factors on its practice is often overlooked. According to a recent report by the US National Institute of Standards and Technology (NIST), the integration of research-based practices can significantly improve the quality and reliability of forensic work.

Human factors and work environments

NIST points out that there are elements, such as lighting, noise or temperature that can affect the concentration of forensic scientists. For example, working in a quiet environment can improve accuracy in DNA analysis. In addition, recognising and learning from mistakes without fear of retaliation fosters a culture of continuous improvement.

Emotional well-being of professionals

Forensic analysts are often confronted with traumatic cases such as child sexual abuse, which can cause stress and trauma. To prevent burnout and maintain job quality, NIST recommends mandatory breaks and case rotations, and access to counselling.

Application in Catalonia

In Catalonia, the Autonomous University of Barcelona promotes good practices in research, including ethics and quality. The Official College of Psychology of Catalonia offers training in forensic evaluation in which the importance of the well-being of professionals is emphasised.

One of the most promising advances in recent forensic science has come not from large international laboratories, but from Catalonia. The scientific police of the Mossos d’Esquadra Corps has developed a pioneering reagent called POSME (Powder Suspension of Mossos d’Esquadra), which allows fingerprints to be detected on traditionally problematic surfaces, such as human skin. This finding, which has been published in the prestigious Journal of Forensic Identification, represents a revolution in the investigation of crimes, especially in cases of sexual violence, where, until now, conclusive physical evidence was often lacking.

POSME combines iron oxide with ethanol, water and polysorbate 80, and is noted for its ability to detect aged prints and on surfaces with contaminants such as blood or lubricants. Its application is simple, and the result is highly effective: after applying the reagent as if it were paint and wiping it off with water, the prints are clearly revealed. The success of this reagent has aroused the interest of police forces from all over the world, such as those from Austria and Mexico, and positions Catalonia as an international benchmark in forensic innovation.

This milestone demonstrates that applied research, when conducted from the field and with specialised technical knowledge, can have a direct and transformative impact on the fight against crime and the improvement of justice.

Towards a stronger forensic science

Adopting evidence-based practices can strengthen forensic science in Catalonia and ensure more reliable results and better administration of justice. It is essential to foster optimal work environments, recognise the importance of emotional well-being and promote a culture of learning and continuous improvement.

For more information, the full NIST report can be found here: https://www.nist.gov/blogs/taking-measure/research-based-practices-can-help-forensic-scientists-do-their-best-work?utm_source=chatgpt.com

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Last February, the research organisation RAND published a report authored by Jim Mitre and Joel B. Predd, in which they warn that the emergence of Generative Artificial Intelligence (GAI) is a real possibility that the U.S. national security community should be taking seriously.

The report identifies five major challenges that Generative Artificial Intelligence may pose to U.S. national security. (1) the development of wonder weapons, (2) systemic shifts in power, (3) the ability of non-experts to create weapons of mass destruction, (4) the emergence of artificial entities with agency, and (5) widespread instability.

All of this poses a number of challenges for strategists and policy and security decision-makers as they try to anticipate the threats and opportunities that could arise both during the process of achieving GAI and once it materialises.

A new technological Manhattan Project?

In 1938, the splitting of the atom started the nuclear arms race. Now, advances in Generative Artificial Intelligence have raised similar fears in the national security sphere. Will it be the next strategic paradigm shift? And, if so, what threats does it pose to global security?

Although GAI is still a hypothesis, its plausibility demands a strategic response from states. The RAND study identifies five major issues that could emerge with the development of GAI:

• Wonder weapons and first-move advantage

The great fear is that GAI could uncover a revolutionary technological breakthrough, enabling the development of unstoppable cyberweapons, hyper-advanced autonomous systems or perfectly optimised military strategies. This could confer a massive advantage to the first nation to gain control of it.

• Systemic shift in global power

GAI could alter the balance of power between nations, not necessarily through weapons, but through its ability to improve productivity, accelerate scientific discovery or redefine global economic dynamics. This could lead to a new world order in which the economies most adaptable to GAI consolidate their dominance.

An added risk is that the concentration of GAI development in a few private companies could give them unprecedented power, altering the traditional relationship between states and corporations.

• Empowerment of non-experts in weapons of mass destruction

If GAI can facilitate the creation of highly lethal biological or cyberweapons, global security will be severely compromised. Current systems have already demonstrated worrying capabilities in this area, and GAI could amplify the risk exponentially.

• Artificial entities with agency

Loss of control over GAI systems could lead to the creation of autonomous artificial entities capable of acting independently. This could pose a risk to critical decision making in sectors such as defence, economics and critical infrastructure management.

• Strategic instability

Before GAI fully arrives, the technology race between states and corporations may provoke tensions similar to the Cold War. The perception that an adversary is on the verge of gaining a decisive advantage could trigger pre-emptive reactions, even armed conflict.

Towards a resilient strategy

The United States and its allies have initiated measures to maintain leadership in AI, but they may prove insufficient if GAI develops in a sudden or disruptive manner.

GAI can redefine the future of global security. This is not just a technical challenge, but a strategic revolution that requires an intelligent and proactive response. Decisions made today will determine whether GAI becomes a stabilising force or an unprecedented threat to humanity.

LINK: https://www.rand.org/pubs/perspectives/PEA3691-4.html??cutoff=true&utm_source=AdaptiveMailer&utm_medium=email&utm_campaign=7014N000001Snj1QAC&utm_term=00v4N00000X46iFQAR&org=1674&lvl=100&ite=2950 a0wQK00000AqgobYAB

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Artificial intelligence (AI) is transforming several fields and biotechnology is no exception. A recent report by the U.S. National Academies of Sciences, Engineering, and Medicine highlights the potential of AI to improve biosecurity but also warns of the risks of its misuse.

The beneficial potential of AI in biosecurity

AI can be a powerful tool for public health. AI models can analyse large amounts of data to help design medical countermeasures that prevent, treat and mitigate health threats, such as drug discovery. This may accelerate the development of vaccines and treatments for infectious diseases, both naturally occurring and those caused by intentional acts.

The risks of misuse of AI in biotechnology

However, the report also warns that AI-enabled biological tools could be used for harmful purposes. For example, AI could design new biological agents with pandemic potential or modify existing viruses or bacteria to make them more harmful or transmissible.

Current capabilities and limitations of biological AI tools

The report assesses the current capabilities of biological AI tools to amplify the benefits or risks of applying biological tools. Currently, no biological AI tool is capable of designing an entirely new virus, and its capabilities to modify an existing infectious agent with potential for epidemic- or pandemic-scale consequences are limited.

The report examines three types of harmful applications:

Design of biomolecules, such as toxins: Available biological AI tools can design and redesign toxins using different amino acids. However, the scale of potential threats would likely be limited to the local level.

Modification of existing pathogens to make them more virulent: Biological AI tools can shape very specific characteristics that can predict virulence-related traits.

Design of a completely new virus: No currently available biological AI tool has the capability to design a new virus.

Recommendations for biosecurity in the age of AI

The report offers several recommendations to mitigate the risks of AI misuse in biotechnology:

• Continuous monitoring and assessment: Government agencies should continually assess and mitigate the risks of AI-enabled biological tools being misused.
• Strategic data collection: Considering the importance of data for AI model training, the report urges strategic collection of AI-ready biological datasets.
• Investment in data infrastructure: Building new national data resources and other forms of infrastructure to support AI should be a research priority for the United States to maintain competitiveness and scientific innovation.
• Investment in research and development: The Departments of Defence, Health and Human Services, Energy, and other U.S. federal agencies should continue to invest in research, data infrastructure and high-performance computing to drive advances in AI and also control potential risks.

Conclusion

AI offers great potential to improve biosecurity and protect us from biological threats. However, it is essential to be aware of the risks of misuse and take proactive measures to mitigate them. Through continuous monitoring, strategic data collection, infrastructure investment and research and development, we can harness the power of AI to make the world a safer place.

Link: https://www.nationalacademies.org/news/2025/03/ai-tools-can-enhance-u-s-biosecurity-monitoring-and-mitigation-will-be-needed-to-protect-against-misuse

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Digital transformation has proven to be a profound game changer in the lives of citizens and businesses in the EU. By identifying the main priorities for EU digital policy to be developed in the next legislative cycle, the Council conclusions aim to address both the challenges and opportunities in the digital sphere.

New technologies have driven innovation, economic growth and sustainability. That being said, a successful digital transformation must be based on a safe, inclusive, sustainable and human-centred approach that upholds democracy and human rights. Digital rights are fundamental for everyone. We must ensure that no one is left behind, offering all Europeans the opportunity to develop essential digital skills and actively participate in the online world.

To improve the EU’s competitiveness on the global stage, a common European approach to innovative digital technologies that strike the right balance between innovation, regulatory burden and protection of the Union’s economic security should be promoted. To achieve these goals, ambitious targets must be set for the future in terms of digital skills, digital governance and secure, digital infrastructure across Europe.

In its conclusions, the Council stresses that effective, consistent and efficient implementation of the recently adopted laws with the minimum administrative burden for public and private actors is the main priority for the next mandate.

A common European approach to innovative digital technologies is of key importance for the competitiveness of the EU and for ensuring the protection of the Union’s economic security, while maintaining economic openness and dynamism.

Member States recognize the importance of ensuring a more secure, responsible and reliable online environment in accordance with the Declaration of Louvain-la-Neuve adopted during the informal meeting of telecommunications ministers on 12 April 2024.

Member States also stress that this digital transformation should go hand in hand with the green transition, accompanied by ambitious sustainability targets.

Strengthening the EU’s competitiveness in the digital transformation requires attracting and retaining a digitally skilled workforce, particularly women, and thus overcoming the digital divide.

The conclusions underline the importance of ensuring a secure and resilient digital infrastructure across the EU.

The Council conclusions also highlight the importance of the international dimension of EU digital policy, welcoming the strengthening of digital partnerships and digital trade agreements and stressing the need to develop a more proactive and coordinated Union approach to playing a key global role in digital transformation and governance.

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It is estimated that, during the year 2022, 13.6 million people in the United States drove at some point under the influence of some type of illicit drugs.

When currently investigating cases of impaired driving and traffic fatalities, the National Safety Council recommends that forensic toxicology laboratories regularly test blood for at least one of the 35 most common drugs behind many of these cases.

However, limitations may interfere with understanding the frequency with which drug use contributes to impaired driving incidents. To better understand this, the researchers funded by the National Institute of Justice from the Center for Forensic Science Research and Education examined blood samples from more than 2,500 cases and created a more detailed picture of how drugs interfere with driving.

Drug-impaired driving is often associated with alcohol consumption and, obviously, this is behind accidents, injuries and fatalities. According to the National Highway Traffic Safety Administration, one person died every 39 minutes in an alcohol-related accident in 2021 in the USA. But alcohol is not the only concern. The use of illicit drugs, legalised drugs such as cannabis and/or the abuse of prescription drugs can also impair a driver’s skills and, for various reasons, this is not being investigated.

These drugs include new emerging psychoactive substances, prescription drugs and traditional drugs of abuse with limited or regional prevalence, many of which require advanced instrumentation for detection. Most laboratories test for Tier 1 drugs, but only test for selected Tier 2 drugs when they are regionally relevant. Therefore, the frequency and types of Tier 2 substances that contribute to drug-impaired driving and fatal crashes are not well understood.

If a sample meets or exceeds a predetermined blood alcohol concentration threshold, some laboratories will not perform any additional drug testing. This cut-off is more commonly 0.08% or 0.10%. The per se proscribed blood alcohol level in the United States in all states is 0.08% (except Utah, where it is 0.05%). Laboratories that adhere to this practice will not detect other drugs that may cause or contribute to impaired driving.

This threshold test may interfere with a complete understanding of drug involvement in driving. Why do so many laboratories use it?

• Toxicology laboratories have limited budgets and resources.
• Risky driving can be explained not only by blood alcohol concentration.
• The lack of penalties for drug use means that it should be measured beyond the BAC level.
• Agencies that use the services of the laboratories have requested this limit.
• The recommendations of the National Security Council are accepted.
• The researchers estimated the frequency with which drugs contribute to the problem, testing 2,514 cases with a range of 850 therapeutic drugs. Randomly selected blood samples from a group of suspected impaired driving cases were examined. Samples were collected in Horsham, Pennsylvania, between 2017 and 2020.

Of the 2,514 suspected cases examined:

• The overall positivity for drugs (Tier 1 or Tier 2 drugs) was 79%, almost double the 40% positive for alcohol.
• A smaller portion of the cases (23%) tested positive for both drugs and alcohol.
• Only 17% of the cases were positive for alcohol alone.
• Natural cannabinoids experienced a statistically significant increase in positivity over the four years of study.

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The mayor of the U.S. city of New York, Eric Adams, a well-known lover of technology, has revealed that drones, these small, unmanned planes, will be used to assist beach guards at Coney Island as part of a pilot program that will begin this summer.

Journalists Dana Rubinstein and Corey Kilgannon reported the story making explicit that, among the hundreds of thousands of people who flock to Coney Island and other New York City public beaches each summer, there are many who cannot swim. And, besides that, many of them bathe even if the beach guards have already left.

This summer, swimmers having trouble in the water in the Coney Island area may encounter not only a young person who can save their lives with an orange swimsuit, but also the help, from the sky, of a large insect-like device that delivers a raft.

This drone with a raft is the latest in a series of devices promoted by the mayor as a way to improve the lives of citizens in New York. Eric Adams had also previously deployed a robot to patrol the Times Square subway station and promoted a lasso-like device to restrain violent or psychotic people.

Although there are still doubts about their operation, the drones will begin flying on an experimental basis this summer in the area considered an entertainment mecca on the south shore of the Brooklyn borough. It should also be added that drone operators will use a powerful loudspeaker attached to their body to communicate with both swimmers in distress and lifeguards attempting the rescue operation.

New York City may be known for many things, but it also boasts 14 miles of urban beaches, from Coney Island to Brooklyn and Rockaway Beach in the Bronx and South Beach on Staten Island.

City officials have long struggled to improve water safety at public beaches, notorious for strong tides, a high percentage of inexperienced swimmers, and poor professional skills among lifeguard service personnel. Four people drowned on city beaches in 2023, all while lifeguards were already off duty, and three in 2022. However, there have been years with more fatalities, such as in 2019 with seven fatalities on Rockaway beaches alone.

Pending the pilot scheme’s entry into operation, Police Department deputy commissioner for operations Kaz Daughtry praised the drones’ ability to drop flotation devices to swimmers in distress.

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